Engineering Commons^™

Physio-Chemical Modifications To Re-Engineer Small Extracellular Vesicles For Targeted Anticancer Therapeutics Delivery And Imaging, Rahmat Asfiya, Lei Xu, Anjugam Paramanantham, Kuanysh Kabytaev, Anna Chernatynskaya, Grace Mccully, Hu Yang, Akhil Srivastava

Chemical and Biochemical Engineering Faculty Research & Creative Works

Cancer theranostics developed through nanoengineering applications are essential for targeted oncologic interventions in the new era of personalized and precision medicine. Recently, small extracellular vesicles (sEVs) have emerged as an attractive nanoengineering platform for tumor-directed anticancer therapeutic delivery and imaging of malignant tumors. These natural nanoparticles have multiple advantages over synthetic nanoparticle-based delivery systems, such as intrinsic targeting ability, less immunogenicity, and a prolonged circulation time. Since the inception of sEVs as a viable replacement for liposomes (synthetic nanoparticles) as a drug delivery vehicle, many studies have attempted to further the therapeutic efficacy of sEVs. This article discusses engineering strategies …

Rab7 Deficiency Impairs Pulmonary Artery Endothelial Function And Promotes Pulmonary Hypertension, Bryce Piper, Srimathi Bogamuwa, Tanvir Hossain, Daniela Farkas, Lorena Rosas, Adam C. Green, Geoffrey Newcomb, Nuo Sun, Jose A. Ovando-Ricardez, Jeffrey C. Horowitz, Aneel R. Bhagwani, Hu Yang, Tatiana V. Kudryashova, Mauricio Rojas

Chemical and Biochemical Engineering Faculty Research & Creative Works

Pulmonary arterial hypertension (PAH) is a devastating and progressive disease with limited treatment options. Endothelial dysfunction plays a central role in the development and progression of PAH, yet the underlying mechanisms are incompletely understood. The endosome-lysosome system is important to maintain cellular health, and the small GTPase RAB7 regulates many functions of this system. Here, we explored the role of RAB7 in endothelial cell (EC) function and lung vascular homeostasis. We found reduced expression of RAB7 in ECs from patients with PAH. Endothelial haploinsufficiency of RAB7 caused spontaneous pulmonary hypertension (PH) in mice. Silencing of RAB7 in ECs induced broad …

Experimental Thermal Conductivity Studies Of Agar-Based Aqueous Suspensions With Lignin Magnetic Nanocomposites, Bishal Gautam, Saja M. Nabat Al-Ajrash, Mohammad Jahid Hasan, Abhishek Saini, Sarah J. Watzman, Esteban Ureña-Benavides, Erick S. Vasquez-Guardado

Chemical and Materials Engineering Faculty Publications

Nanoparticle additives increase the thermal conductivity of conventional heat transfer fluids at low concentrations, which leads to improved heat transfer fluids and processes. This study investigates lignin-coated magnetic nanocomposites (lignin@Fe₃O₄) as a novel bio-based magnetic nanoparticle additive to enhance the thermal conductivity of aqueous-based fluids. Kraft lignin was used to encapsulate the Fe₃O₄ nanoparticles to prevent agglomeration and oxidation of the magnetic nanoparticles. Lignin@Fe₃O₄ nanoparticles were prepared using a pH-driven co-precipitation method with a 3:1 lignin to magnetite ratio and characterized by X-ray diffraction, FT-IR, thermogravimetric analysis, and transmission electron …

Human Factors In Aviation Maintenance: Understanding Errors, Management, And Technological Trends, Rajee Olaganathan

Publications

Aircraft maintenance and inspection are complex systems that work on a time-based schedule and require teamwork of different professionals to maintain the airworthiness of aircraft. Errors in maintenance and inspection processes cause in-flight engine shutdowns, flight delays, flight cancellation, sometimes resulting in accidents and incidents that cause significant economic consequences. Due to the substantial impact on both safety and financial aspects of an air carrier, this paper focuses on hangar maintenance as the work is carried out across several shifts by different technicians, addressing various human factor issues that contribute to errors. The paper will also briefly discuss shift work …

Radiation-Induced Polymerization Of Thermo-Responsive Polymers And Comprehensive Characterization For Improved Performance, Attia Attia, Islam Mohamed Eng., Mohamed El-Deab Prof., Nabila Maziad Prof.

Petroleum Engineering and Gas

Early water breakthrough with high water cut through highly conductive thief zones is a prevalent problem in many water-flooded oil reservoirs. Smart polymers that are sensitive to temperature changes, also known as thermo-responsive polymers, e.g., polyethylene glycol (PEG) have great advantages over conventional polymers that can be exploited to solve the problem of conductive thief zones. Thus, this study aims at designing and synthesizing a thermo-responsive polymer using Gamma Ray Induced radiation with good tolerance against high temperature, and high salinity reservoir conditions with feasible and economic synthesis procedure for application in Egyptian oil reservoirs. That is a combined use …

Pisa Printing Microneedles With Controllable Aqueous Dissolution Kinetics, Aaron Priester, Jimmy Yeng, Yuwei Zhang, Krista Hilmas, Risheng Wang, Anthony J. Convertine

Chemistry Faculty Research & Creative Works

This study focused on the development of high-resolution polymeric structures using polymer-induced self-assembly (PISA) printing with commercially available digital light-processing (DLP) printers. Significantly, soluble solids could be 3D-printed using this methodology with controllable aqueous dissolution rates. This was achieved using a highly branched macrochain transfer agent (macro-CTA) containing multiple covalently attached CTA groups. In this work, the use of acrylamide as the self-assembling monomer in isopropyl alcohol was explored with the addition of N-(butoxymethyl)acrylamide to modulate the aqueous dissolution kinetics. PISA-printed microneedles were observed to have feature sizes as small as 27 μm, which was close to the resolution limit …

Advanced Shape Memory Alloy Fibers Designed To Enhance Crack Closure And Re-Centring Performance In Cement-Based Composites, Ayoub Dehghani, Farhad Aslani

Research outputs 2022 to 2026

Crack-closing and re-centring attributes were observed in cementitious composites utilising segmented pseudoelastic shape memory alloy fibres (S-PSMAFs) developed in this study. S-PSMAFs, produced via laboratory deep drawing, displayed notable strain recovery capacity during detwinning and martensite phases in direct cyclic tensile tests. Cementitious composites incorporating S-PSMAFs at 0.5%, 0.75%, and 1.0% dosages underwent testing in static and cyclic flexure using both unnotched and notched beams. Results were compared with steel fibre (SF) reinforced specimens. Digital image correlation (DIC) provided full-field strain maps and crack propagation data. The cyclic testing allowed assessment of crack-closing and re-centring behaviour at varying deflections post-cracking …

Intellectual Property Rights And Copyright Laws In The Regime Of Artificial Intelligence (Ai) In India, Hemavathy C

Library Philosophy and Practice (e-journal)

Artificial Intelligence (AI) has been developing for two decades. The application of AI is budding quickly in business dealings, corporate communication and legal services. AI and Law Forms are increasingly important in the legal arena as they play a significant role in the economy and society. Scientists and policymakers together are facing some of the hardest problems with the advancement of machine learning, cryptology and data protection. This paper is very helpful for policymakers, economists, lawyers and technocrats in the aspect of the ethical use of AI in data protection, privacy, security and social corners turns into very relevant issues …

Retraction Of Numerical Modeling Of An L-Shaped Very Stiff Concrete Retaining Wall, Mej Editorial Board

Mansoura Engineering Journal

This is a Retraction note

Understanding Quadrature Modulation By Designing A 7mhz Iq Test Bench To Encode The Polybius Square, William Lee Bradley

Dissertations and Theses

This thesis outlines the design of an IQ Test Bench that allows for experimentation of quadrature modulation techniques. Quadrature modulation utilizes two signals I and Q, 90° out of phase from each other, to greatly increase communication data rates. Using Desmos, a thorough mathematical analysis of waveform mixing is presented, and constellation diagrams are plotted from the results. From this an ancient fire signaling technique known as the Polybius Square is encoded into the system. The IQ Test Bench is built from fundamental components that would be contained within an RFFE: a local oscillator and two frequency mixers. The LO …

Customer Churn Prediction Based On Sentiment Score, Shadha Al-Safi

Theses and Dissertations

In recent years, the telecommunications industry has witnessed intensified competition, wherein the expense associated with acquiring new consumers exceeds that of sustaining existing ones. Consequently, predicting customer churn prior to its occurrence has become essential. This study proposes a sentiment-based customer churn prediction model in which the sentiment of customers is predicted using Random Forest. Subsequently, the derived sentiment predictions are combined with additional features to predict customer churn. The ensemble technique is applied to predict churn, consisting of K-nearest neighbors, Support Vector Machines, Random Forest as base learners, and Multiple Layer Perceptron as a meta learner. Moreover, mutual information …

A Tale Of Two Low-Income, First-Generation Engineering Students: Well-Being, Belonging, And The Role Of Chosen Family, Justin C. Major

First-Generation Symposium

Belonging has been identified as an important, if not the most important, factor impacting the success of college students, especially (multi)marginalized students in engineering programs. Well-being and belonging are deeply entwined, helping to explain how the strength of students affinities lead them to feel a sense of true happiness that guide their holistic success. In this presentation, I present two differing narrative stories from Samantha and Rocky, two non-white, low-income, first-generation women in engineering. At the time of their narratives, both women were in the fourth year of their engineering degrees; however, Samantha was graduating and Rocky was not. In …

Transfer Learning In The Era Of Foundational Models: Application To Diagnosis In Rheumatology, Prashant Shekhar

Math Department Colloquium Series

Problems with current synovitis grading procedures

• There has been a lack of reliability in grading these images in the medical community due to a lack of universally accepted diagnostic criteria [Momtazmanesh et al., 2022]
• The human/machine variability creates an additional challenge in an efficient automated scoring system [Ranganath et al., 2022]
• There is a lack of consistency between doctors in grading these images [Momtazmanesh et al., 2022]

History Of Clover Leaf Syndrome, Isabella Perez

Mako: NSU Undergraduate Student Journal

The purpose of this paper is to summarize the history of clover leaf syndrome and describe the newest advancements made to treat it. Clover leaf syndrome is more formally referred to as Kleeblattschadel syndrome. Information was gathered from several scholarly, peer-reviewed articles, and was condensed down into the key takeaways. This syndrome impacts the formation of the skull due to premature fusion of its sutures, creating a tri-lobar skull that resembles a clover leaf. This premature fusion is referred to as a type of craniosynostosis and has been linked to causing several other health complications ranging in severity. This is …

Extraterrestrial Life: The Possibility Of A Human-Alien Interaction, Ariana M. Piscoya

CAFE Symposium 2024

We all have heard of at least one case where someone assured having seen a flying extraterrestrial object. There are thousands of thousands of videos we can find online that “prove” the existence of aliens. In the hypothetical case where aliens are really out there, why haven't we been able to talk to them and look at them face-to-face? A human-extraterrestrial interaction has not yet been achieved for two reasons. First, alien energy is much more powerful than that of humans, so it would require thousands of thousands of years for the human race to develop a technology able to …

Fractional Delay-Dependent Load Frequency Controller Design For A Single-Area Power System With Communication Delay, Erhan Yumuk

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a fractional delay-dependent load frequency control design approach for a single-area power system with communication delay based on gain and phase margin specifications. In this approach, the closed-loop reference transfer function relies on the delayed Bode’s transfer function. The gain and phase margin specifications are established in order to optimize the reference model based on three time-domain performance indices. Here, a category of fractional-order model is employed to describe the single-area power system incorporating communication delay. The controller parameters are determined using the fractional-order system model and optimal closed-loop reference model. Then, a delay-dependent control mechanism is …

Motion Magnification-Inspired Feature Manipulation For Deepfake Detection, Aydamir Mirzayev, Hamdi Di̇bekli̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Recent advances in deep learning, increased availability of large-scale datasets, and improvement of accelerated graphics processing units facilitated creation of an unprecedented amount of synthetically generated media content with impressive visual quality. Although such technology is used predominantly for entertainment, there is widespread practice of using deepfake technology for malevolent ends. This potential for malicious use necessitates the creation of detection methods capable of reliably distinguishing manipulated video content. In this work we aim to create a learning-based detection method for synthetically generated videos. To this end, we attempt to detect spatiotemporal inconsistencies by leveraging a learning-based magnification-inspired feature manipulation …

Error Performance Enhancement And Complexity Reduction In Ofdm Systems Via Coordinate Interleaving Under Practical Impairments, Mustafa Anıl Reşat, Armed Tusha, Seda Doğan Tusha, Serdar Özyurt, Hüseyin Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, subcarrier coordinate interleaving (CI) is implemented to orthogonal frequency division multiplexing (OFDM) systems with the aim of both enhancing the error performance and reducing the implementation complexity. To this end, the modulated symbols are independently chosen from a modified M-ary amplitude-shift keying signal constellation under a specific CI strategy. In addition to doubling the diversity level of the original OFDM scheme, the adopted CI approach also drastically reduces the inverse fast Fourier transform (IFFT) size at the transmit side by guaranteeing the first half of the input vector to be identical with the second half at the …

Artificial Intelligence-Based Evaluation Of The Factors Affecting The Sales Of An Iron And Steel Company, Mehmet Pekkaya, Zafer Uysal, Aytaç Altan, Seçkin Karasu

Turkish Journal of Electrical Engineering and Computer Sciences

It is important to predict the sales of an iron and steel company and to identify the variables that influence these sales for future planning. The aim in this study was to identify and model the key factors that influence the sales volume of an iron and steel company using artificial neural networks (ANNs). We attempted to obtain an integrated result from the performance/sales levels of 5 models, to use the ANN approach with hybrid algorithms, and also to present an exemplary application in the base metals industry, where there is a limited number of studies. This study contributes to …

Fast Grid Search: A Grid Search-Inspired Algorithm For Optimizing Hyperparameters Of Support Vector Regression, Mustafa Açikkar

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents a fast hyperparameter optimization algorithm based on the benefits and shortcomings of the standard grid search (GS) algorithm for support vector regression (SVR). This presented GS-inspired algorithm, called fast grid search (FGS), was tested on benchmark datasets, and the impact of FGS on prediction accuracy was primarily compared with the GS algorithm on which it is based. To validate the efficacy of the proposed algorithm and conduct a comprehensive comparison, two additional hyperparameter optimization techniques, namely particle swarm optimization and Bayesian optimization, were also employed in the development of models on the given datasets. The evaluation of …

Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk

Turkish Journal of Electrical Engineering and Computer Sciences

Mixed-integer linear programming (MILP) techniques are widely used in cryptanalysis, aiding in the discovery of optimal linear and differential characteristics. This paper delves into the analysis of block ciphers KLEIN and PRINCE using MILP, specifically calculating the best linear and differential characteristics for reduced-round versions. Both ciphers employ matrix multiplication in their diffusion layers, which we model using multiple XOR operations. To this end, we propose two novel MILP models for multiple XOR operations, which use fewer variables and constraints, proving to be more efficient than standard methods for XOR modeling. For differential cryptanalysis, we identify characteristics with a probability …

Differentially Private Online Bayesian Estimation With Adaptive Truncation, Sinan Yildirim

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a novel online and adaptive truncation method is proposed for differentially private Bayesian online estimation of a static parameter regarding a population. A local differential privacy setting is assumed where sensitive information from individuals is collected on an individual level and sequentially. The inferential aim is to estimate, on the fly, a static parameter regarding the population to which those individuals belong. We propose sequential Monte Carlo to perform online Bayesian estimation. When individuals provide sensitive information in response to a query, it is necessary to corrupt it with privacy-preserving noise to ensure the privacy of those …

A Novel Extended Reaction Force/Torque Observer With Impedance Control, İlkay Turaç Özçeli̇k, Abdurrahman Eray Baran

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a new extended version of the reaction force observer (RFOB) for high-precision motion control systems. The RFOB has been proven to be useful for many applications in the literature. However, because of the low-pass filter present inside of the RFOB, it has certain limitations. In this study, a new algorithm is proposed to compensate for filtering-based errors in the classical RFOB structure. The algorithm includes the differentiation of the observed force and scaling with a proper value. However, since the force has a noisy nature, differentiation also affects the signal’s stability and performance. To resolve this issue, …

Traffic Signal Optimization Using Multiobjective Linear Programming For Oversaturated Traffic Conditions, Mustafa Murat Coşkun, Cevat Şener, İsmail Hakkı Toroslu

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we present a framework designed to optimize signals at intersections experiencing oversaturated traffic conditions, utilizing mixed-integer linear programming (MILP) techniques. The proposed MILP solutions were developed with different objective functions, namely a reduction in the total remaining queue and fair distribution of the remaining queue after each signal cycle. Our framework contains two distinct stages. The initial stage applies two distinct MILP methodologies, while the subsequent stage employs a neighborhood search method to further reduce the delays associated with the green signal timings derived from the first stage. Ultimately, to evaluate their effectiveness across various intersections, we …

Grey Wolf Optimization Algorithm-Based Robust Neural Learning Control Of Passive Torque Simulators With Predetermined Performance, Seyyed Amirhossein Saadat, Mohammad Mehdi Fateh, Javad Keighobadi

Turkish Journal of Electrical Engineering and Computer Sciences

In flight control systems, the actuators need to tolerate aerodynamic torques and continue their operations without interruption. To this end, using the simulators to test the actuators in conditions close to the real flight is efficient. On the other hand, achieving the guaranteed performance encounters some challenges and practical limitations such as unknown dynamics, external disturbances, and state constraints in reality. Thus, this article attempts to present a robust adaptive neural network learning controller equipped with a disturbance observer for passive torque simulators (PTS) with load torque constraints. The radial basis function networks (RBFNs) are employed to identify the unknown …

Automated Identification Of Vehicles In Very High-Resolution Uav Orthomosaics Using Yolov7 Deep Learning Model, Esra Yildirim, Umut Güneş Seferci̇k, Taşkın Kavzoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The utilization of remote sensing products for vehicle detection through deep learning has gained immense popularity, especially due to the advancement of unmanned aerial vehicles (UAVs). UAVs offer millimeter-level spatial resolution at low flight altitudes, which surpasses traditional airborne platforms. Detecting vehicles from very high-resolution UAV data is crucial in numerous applications, including parking lot and highway management, traffic monitoring, search and rescue missions, and military operations. Obtaining UAV data at desired periods allows the detection and tracking of target objects even several times during a day. Despite challenges such as diverse vehicle characteristics, traffic congestion, and hardware limitations, the …

Life During Wartime: Proactive Cybersecurity Is A Humanitarian Imperative, Stanley Mierzwa, Diane Rubino

Center for Cybersecurity

In brief:

• Humanitarian agencies responding to conflict face massive challenges in distributing aid. Cyberattacks add to that burden.
• This short overview, tailored for non-technical leaders, demystifies the process and equips clouds security experts to proactively champion cloud security at non-profits, and non-governmental organizations.

Proactive Cybersecurity is a Humanitarian Imperative | CSA (cloudsecurityalliance.org)

A Fractal Art Approach To The Three-Body Problem, Charles F. Babbs

Weldon School of Biomedical Engineering Faculty Working Papers

This preliminary study explores a new search strategy for identifying relatively stable vs. unstable solutions to the planar three-body problem in astrophysics, starting from the perspective of computer-generated art. Here classical Newtonian accelerations, speeds, and positions of all three bodies in a fixed plane are calculated. All three bodies are stationary at time zero, and the fate of the system is classified as reflecting either a bound stable orbit, a likely collision, or the ejection of one body. The initial position of one of the three bodies is varied in the image plane, and the outcome coded as one of …

Sampling-Accelerated Prediction Of Phonon Scattering Rates For Converged Thermal Conductivity And Radiative Properties, Ziqi Guo, Zherui Han, Dudong Feng, Guang Lin, Xiulin Ruan

Purdue University Libraries Open Access Publishing Fund

The prediction of thermal conductivity and radiative properties is crucial. However, computing phonon scattering, especially for four-phonon scattering, could be prohibitively expensive, and the thermal conductivity for silicon after considering four-phonon scattering is significantly under-predicted and not converged in the literature. Here we propose a method to estimate scattering rates from a small sample of scattering processes using maximum likelihood estimation. The calculation of scattering rates and associated thermal conductivity and radiative properties are dramatically accelerated by three to four orders of magnitude. This allows us to use an unprecedented q-mesh (discretized grid in the reciprocal space) of 32 × …

Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai

Turkish Journal of Electrical Engineering and Computer Sciences

Alzheimer’s disease (AD) is an illness that involves a gradual and irreversible degeneration of the brain. It is crucial to establish a precise diagnosis of AD early on in order to enable prompt therapies and prevent further deterioration. Researchers are currently focusing increasing attention on investigating the potential of machine learning techniques to simplify the automated diagnosis of AD using neuroimaging. The present study involved a comparison of models for the detection of AD through the utilization of 2D image slices obtained from magnetic resonance imaging brain scans. Five models, namely ResNet, ConvNeXt, CaiT, Swin Transformer, and CVT, were implemented …